•  Provides the ability to assess and simulate sensors upfront, early, and virtually in operationally relevant environments with validated sensor performance models to understand performance tradeoffs, inform investment decisions, and reduce costly testing.

  • Emulates multiple sensors in disparate locations, in realistic scenarios, to provide an environment in which to test, train, and perform analysis. Encapsulates sensor-specific functionality in Device Personality Modules (DPM), allowing for rapid development of new simulators; providing holistic network visibility fostering common components, interoperability, standardization, and reuse.

  • Enables an analytical, process-based approach to improve all aspects of the research and development acquisition earlier in potential or existing program lifecycle(s).

  • Provides the ability to create and tweak new virtual sensor personalities to “what-if” a conjectural benefit before investing in a new sensor development program.

  • Enhances and transforms hazard understanding and decision support by utilizing simulation and analytics to look forward into the battlespace and then bring those results back to the acquisition cycle to better inform capability investment decisions and change recommendations (e.g. DOTMLPF-P).

  • Enables performance tradeoff analysis by making updates to existing sensor personalities and creating new ones (e.g., "good as is", "worth updating the sensor based on findings", "sensor is fine but recommend updates to CONOPS and/or DOTMLPF-P", "sensor still false alarms too much but can be reduced by taking actions x, y, z or adding another sensor type and correlating").

  • Allows for optimization of sensor type and quantity as a function of mission scenarios with objective and threshold requirements.

  • Shows operational commanders and users the benefits and risks of having certain sensors in certain environments. 

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